X=['Consumer expenditure household','Consumer public adm','Equip. Goods others','Const.',
   'Total exports goods and services','Total imports goods and services','trad_op',
   'Domestic_Demand_per_GDP_wc']
X=df[X]
y=df.GDP
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
lm = LinearRegression()
lm.fit(X_train,y_train)
print(lm.score(X_test,y_test))
print(sqrt(mean_squared_error(y_test,lm.predict(X_test))))